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Role Description

We are looking for a Principal ML Scientist to advance the state of our computer vision systems for warehouse inventory scanning. You will work across the full ML lifecycle — from research and model architecture through training, deployment, and production monitoring — with a focus on delivering measurable improvements to detection, segmentation, and OCR accuracy across our drone and MHE Vision products.

• Advance core computer vision model performance (object detection, segmentation, OCR) for warehouse inventory scanning across drone and MHE Vision platforms
• Own the full ML lifecycle from research and experiment design through production deployment and monitoring — applying rigorous ablation studies and SOTA methodology
• Collaborate with the ML infrastructure team on model optimization and deployment across cloud and edge inference targets (ONNX, TensorRT, quantization)
• Work with Operations and Product to understand customer needs and translate them into ML improvements with measurable business impact
• Provide technical leadership and mentorship to the ML team, raising standards for experiment design, model evaluation, and production readiness
• Explore next-generation perception capabilities, including embedded and on-prem inference optimization for new deployment targets

Qualifications

• 10+ years of experience in machine learning or computer vision
• Deep expertise in CNNs, object detection, image segmentation, and OCR using PyTorch (preferred) or TensorFlow
• Strong Python proficiency and software engineering fundamentals; hands-on experience with OpenCV and GPU computing
• Track record of delivering production ML systems at scale, including model training, evaluation, and deployment
• MS or PhD in Computer Science, Machine Learning, Robotics, or a related field

Requirements

• Experience with drone, robotics, or autonomous systems perception
• Publications in top vision or robotics conferences (CVPR, ICCV, ICRA, NeurIPS, CoRL)
• Experience designing and deploying models for real-time inference on constrained compute platforms
• Warehouse, logistics, or supply chain domain experience